A collaborative design method for satellite module component assignment and layout optimization

2019 ◽  
Vol 233 (15) ◽  
pp. 5471-5491
Author(s):  
Feng-Zhe Cui ◽  
Chong-Quan Zhong ◽  
Xiu-Kun Wang ◽  
Hong-Fei Teng
Keyword(s):  
Collaborative Design ◽  
Optimization Design ◽  
Optimization Problems ◽  
Design Method ◽  
Layout Optimization ◽  
Solution Set ◽  
Pareto Solution ◽  
Multi Objective ◽  
Component Layout ◽  
Assignment Scheme

The collaborative design of the multi-module satellite component (equipment) assignment and layout is the key aspect of the overall satellite design, and the two parts are closely related. In the past, satellite module component layout optimization usually adopted fixed component assignments, which remained constant in the layout optimization stage. If the components were improperly distributed in these modules, it would seriously affect the layout optimization. To overcome this disadvantage, a collaborative design method for the component assignment and layout design is presented for the multi-module (or multi-bearing plate) satellite component layout problem, based on a multi-agent system. First, the component assignment agent adopted a multi-objective optimization method (the non-dominated sorting genetic algorithm II, NSGA-II) to obtain the approximate Pareto solution set of the satellite component assignment scheme. Second, it adopted a fuzzy multi-objective decision method to select a high-quality component assignment scheme from the approximate Pareto solution set. Third, the layout agent employed a dual system co-evolutionary method for the layout optimization design. In the process of the layout optimization, the layout result is fed back to the component assignment design, and the component assignment is adjusted according to the result of the layout optimization. Thus, the above process is continually iterated to achieve the optimal collaborative design of the component assignment and the layout. The proposed method is applied to a simplified multi-module satellite component assignment and layout optimization problem and aims to provide a reference and technical support for other similar multi-module equipment assignment and layout optimization problems.

Multi-Objective Optimization for the Section Structure of Sandwich Plate Applied in the High-Speed Train Compartments

2014 ◽  
Vol 597 ◽  
pp. 535-539
Author(s):  
Yi Qing Wang ◽  
Xu Chen ◽  
Bin Wang ◽  
Xin Bin Kuang ◽  
Xiao Geng Tian
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Sandwich Plate ◽  
Side Wall ◽  
Response Surfaces ◽  
Solution Set ◽  
Multi Objective Optimization ◽  
High Speed Train ◽  
Pareto Solution ◽  
Multi Objective

In order to obtain the side walls section structures of high speed train applicable to different running speeds and conditions, a multi-objective optimization design is made based on the structure of topology optimization. In this optimization formulation, the weight of sandwich plate, static compliance and maximum deformation are used as the objective functions; the thickness of face panels and cores in five parts of the side wall are variables; and the air pressure gradient in compartments is the constraint function. Surrogate model techniques are adopted for constructing the response surfaces based on the optimization. Finally, a multi-objective optimization is performed using the NSGA-II algorithm and the optimization generates a Pareto solution set. The structure performance in Pareto set is greatly improved by 8.21% -33.58% than that of topology structure. In addition, the Pareto solution set provides engineers with many alternative Pareto-optimal solutions for optimization design of the sandwich plate section applied in the high-speed train.

Study on Multi-Objective Optimization Design Method for SRHSC Beams

2011 ◽  
Vol 243-249 ◽  
pp. 362-365
Author(s):  
Shan Suo Zheng ◽  
Yi Hu ◽  
Qing Lin Tao ◽  
Zhi Qiang Li ◽  
Lei Li
Keyword(s):  
Optimization Design ◽  
Optimization Problems ◽  
Design Method ◽  
High Strength ◽  
Shear Capacity ◽  
Structure Design ◽  
Complex Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Design Variables

According to the thought of engineering optimization and the theory of composite structure design, the minimum of the project cost and the maximum of the diagonal shear capacity are taken as the optimization objectives whose importance can be adjusted by weighting factors and the linear weighted method is used to establish evaluation function which changes multi-objective into single-objective in optimization. Taking the various constraints into consideration and choosing the sensitive design variables, the mathematical model of the multi-objective optimization design for steel reinforced high-strength concrete beams is provided. Based on the optimization thought of the Complex Method, the nonlinear optimization problems are solved by MATLAB program.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

scholarly journals Structure of Pareto Solutions of Generalized Polyhedral-Valued Vector Optimization Problems in Banach Spaces

2013 ◽  
Vol 2013 ◽  
pp. 1-10
Author(s):  
Qinghai He ◽  
Weili Kong
Keyword(s):  
Banach Spaces ◽  
Vector Optimization ◽  
Optimization Problems ◽  
Vector Optimization Problem ◽  
Solution Set ◽  
Pareto Optimal ◽  
Pareto Solution ◽  
Value Set ◽  
Set Valued Mapping ◽  
Optimal Value

In general Banach spaces, we consider a vector optimization problem (SVOP) in which the objective is a set-valued mapping whose graph is the union of finitely many polyhedra or the union of finitely many generalized polyhedra. Dropping the compactness assumption, we establish some results on structure of the weak Pareto solution set, Pareto solution set, weak Pareto optimal value set, and Pareto optimal value set of (SVOP) and on connectedness of Pareto solution set and Pareto optimal value set of (SVOP). In particular, we improved and generalize, Arrow, Barankin, and Blackwell’s classical results in Euclidean spaces and Zheng and Yang’s results in general Banach spaces.

Applications of Multiple Objective Genetic Algorithms in the Optimization Design of Tracked Self-Moving Power’s Layout

2013 ◽  
Vol 307 ◽  
pp. 161-165
Author(s):  
Hai Jin ◽  
Jin Fa Xie
Keyword(s):  
Optimization Design ◽  
Pareto Front ◽  
Layout Optimization ◽  
Multiple Objective ◽  
Multi Objective Optimization ◽  
Layout Problem ◽  
Basic Principles ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Set Up

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.

scholarly journals Multi-Objective Bee Swarm Optimization Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems

Mathematics ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 133
Author(s):  
Nien-Che Yang ◽  
Danish Mehmood
Keyword(s):  
Power Systems ◽  
Optimization Problems ◽  
Filter Design ◽  
Manhattan Distance ◽  
Multi Objective Optimization ◽  
Optimal Method ◽  
Pareto Solution ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Passive Power

Harmonic distortion in power systems is a significant problem, and it is thus necessary to mitigate critical harmonics. This study proposes an optimal method for designing passive power filters (PPFs) to suppress these harmonics. The design of a PPF involves multi-objective optimization. A multi-objective bee swarm optimization (MOBSO) with Pareto optimality is implemented, and an external archive is used to store the non-dominated solutions obtained. The minimum Manhattan distance strategy was used to select the most balanced solution in the Pareto solution set. A series of case studies are presented to demonstrate the efficiency and superiority of the proposed method. Therefore, the proposed method has a very promising future not only in filter design but also in solving other multi-objective optimization problems.

scholarly journals Multi-Objective Robust Optimization Using a Postoptimality Sensitivity Analysis Technique: Application to a Wind Turbine Design

2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Weijun Wang ◽  
Stéphane Caro ◽  
Fouad Bennis ◽  
Ricardo Soto ◽  
Broderick Crawford
Keyword(s):  
Sensitivity Analysis ◽  
Robust Optimization ◽  
Wind Turbine ◽  
Optimization Design ◽  
Optimization Problems ◽  
Design Environment ◽  
Multi Objective ◽  
Pareto Ranking ◽  
Analysis Technique ◽  
Robust Optimization Design

Toward a multi-objective optimization robust problem, the variations in design variables (DVs) and design environment parameters (DEPs) include the small variations and the large variations. The former have small effect on the performance functions and/or the constraints, and the latter refer to the ones that have large effect on the performance functions and/or the constraints. The robustness of performance functions is discussed in this paper. A postoptimality sensitivity analysis technique for multi-objective robust optimization problems (MOROPs) is discussed, and two robustness indices (RIs) are introduced. The first one considers the robustness of the performance functions to small variations in the DVs and the DEPs. The second RI characterizes the robustness of the performance functions to large variations in the DEPs. It is based on the ability of a solution to maintain a good Pareto ranking for different DEPs due to large variations. The robustness of the solutions is treated as vectors in the robustness function space (RF-Space), which is defined by the two proposed RIs. As a result, the designer can compare the robustness of all Pareto optimal solutions and make a decision. Finally, two illustrative examples are given to highlight the contributions of this paper. The first example is about a numerical problem, whereas the second problem deals with the multi-objective robust optimization design of a floating wind turbine.

scholarly journals Bézier Simplex Fitting: Describing Pareto Fronts of´ Simplicial Problems with Small Samples in Multi-Objective Optimization

2019 ◽  
Vol 33 ◽  
pp. 2304-2313 ◽  
Author(s):  
Ken Kobayashi ◽  
Naoki Hamada ◽  
Akiyoshi Sannai ◽  
Akinori Tanaka ◽  
Kenichi Bannai ◽  
...  
Keyword(s):  
Sample Size ◽  
Optimization Problems ◽  
Solution Set ◽  
Small Samples ◽  
High Dimensional ◽  
Large Sample Size ◽  
Multi Objective Optimization ◽  
Dimensional Solution ◽  
Multi Objective ◽  
Simplex Model

Multi-objective optimization problems require simultaneously optimizing two or more objective functions. Many studies have reported that the solution set of an M-objective optimization problem often forms an (M − 1)-dimensional topological simplex (a curved line for M = 2, a curved triangle for M = 3, a curved tetrahedron for M = 4, etc.). Since the dimensionality of the solution set increases as the number of objectives grows, an exponentially large sample size is needed to cover the solution set. To reduce the required sample size, this paper proposes a Bézier simplex model and its fitting algorithm. These techniques can exploit the simplex structure of the solution set and decompose a high-dimensional surface fitting task into a sequence of low-dimensional ones. An approximation theorem of Bézier simplices is proven. Numerical experiments with synthetic and real-world optimization problems demonstrate that the proposed method achieves an accurate approximation of high-dimensional solution sets with small samples. In practice, such an approximation will be conducted in the postoptimization process and enable a better trade-off analysis.

Multi-Objective Optimal Design of a Double Circular Gear Based on the Differential Evolution Algorithm

2014 ◽  
Vol 977 ◽  
pp. 365-369
Author(s):  
Li Mei Zou ◽  
Bo Guo ◽  
Xue Yi Qian
Keyword(s):  
Differential Evolution ◽  
Optimization Design ◽  
Design Method ◽  
Optimization Technique ◽  
Differential Evolution Algorithm ◽  
Research Process ◽  
Multi Objective Optimization ◽  
Design Quality ◽  
Multi Objective ◽  
Technical And Economic Indicators

In order to improve the comprehensive technical and economic indicators of a double circular gear, based on the conjugate principle and design method of the double circular gear, by use of the modified differential evolution multi-objective optimization technique and MATLAB computer simulation technology, constrained multi-objective optimization design of a double circular gear was done. According to the research process and results, by use of the improved differential evolutionary multi-objective optimization technique, the design cycle of product can be shorten effectively, the design quality of product can be improved.

Optimization of Control Parameters Based on Multi-Objective Genetic Algorithms for Spacecraft Large Angle Attitude

2014 ◽  
Vol 538 ◽  
pp. 470-475 ◽  
Author(s):  
Qiang Huang ◽  
Jian Xin Zhang ◽  
Qiang Zhang ◽  
Xiao Peng Wei
Keyword(s):  
Optimization Design ◽  
Design Method ◽  
Large Angle ◽  
Weight Coefficient ◽  
Control Parameters ◽  
Multi Objective ◽  
Novel Approach ◽  
Attitude Maneuver ◽  
Nonlinear Dynamics Model ◽  
Optimizing Control

Based on multi-objective generic algorithms, a novel approach to optimizing control parameters for large angle spacecraft attitude was proposed. The large angle attitude maneuver controller was designed by taking the spacecraft nonlinear dynamics model and Lyapunov method. To optimize the controller parameters, the alterable weight coefficient method was adopted. Optimal value of time and power consumption acted as fitness goals of the algorithm. Simulation results showed that the algorithm proposed in this paper was superior to the traditional single-objective optimization design method.

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